Facial emotion recognition using enhanced multi-verse optimizer method

In recent years, facial emotion recognition has gained significant improvement and attention. This technology utilizes advanced algorithms to analyze facial expressions, enabling computers to detect and interpret human emotions accurately. Its applications span over a wide range of fields, from improving customer service through sentiment analysis, to enhancing mental health support by monitoring emotional states. However, there are several challenges in facial emotion recognition, including variability in individual expressions, cultural differences in emotion display, and privacy concerns related to data collection and usage. Lighting conditions, occlusions, and the need for diverse datasets also impacts accuracy. To solve these issues, an enhanced multi-verse optimizer (EMVO) technique is proposed to improve the efficiency of recognizing emotions. Moreover, EMVO is used to improve the convergence speed, exploration-exploitation balance, solution quality, and the applicability in different types of optimization problems. Two datasets were used to collect the data, namely YouTube and surrey audio-visual expressed emotion (SAVEE) datasets. Then, the classification is done using the convolutional neural networks (CNN) to improve the performance of emotion recognition. When compared to the existing methods shuffled frog leaping algorithm-incremental wrapper-based subset selection (SFLA-IWSS), hierarchical deep neural network (H-DNN) and unique preference learning (UPL), the proposed method achieved better accuracies, measured at 98.65% and 98.76% on the YouTube and SAVEE datasets, respectively

Biosynthesis of silver nanoparticles derived Acorus Calamus rhizome extract and their biomedical application

The silver nanoparticles (Ag NPs) were derived from Acorus calamus (A. calamus) rhizome extract using different temperature. The absorbance centered at 439 nm, which was corresponds to the wavelength of the surface plasmon resonance of Ag NPs at 95 ◦C. From FESEM and TEM image showed, the Ag NPs were exhibited spherical structure. Elemental compositions were identified by EDAX analysis. The synthesized Ag NPs, functional groups were identified by the FTIR spectra. The antibacterial studies performed against a set of bacterial strains showed that the Ag NPs possessed a greater antibacterial effect than the Plant extract (PE) and silver nitrate. In-vitro cytotoxic effect of green synthesized A. calamus rhizome extract derived Ag NPs tested against MG 63, MCF-7 and HeLa cell lines